https://doi.org/10.1140/epjc/s10052-020-8166-5
Regular Article - Experimental Physics
Study of central exclusive
π
+
π
−
production in proton-proton
collisions at
√
s
= 5.02 and 13 TeV
CMS Collaboration∗
CERN, 1211 Geneva 23, Switzerland
Received: 5 March 2020 / Accepted: 17 June 2020 © CERN for the benefit of the CMS collaboration 2020
Abstract Central exclusive and semiexclusive production ofπ+π−pairs is measured with the CMS detector in proton-proton collisions at the LHC at center-of-mass energies of 5.02 and 13 TeV. The theoretical description of these non-perturbative processes, which have not yet been measured in detail at the LHC, poses a significant challenge to mod-els. The two pions are measured and identified in the CMS silicon tracker based on specific energy loss, whereas the absence of other particles is ensured by calorimeter infor-mation. The total and differential cross sections of exclusive and semiexclusive centralπ+π− production are measured as functions of invariant mass, transverse momentum, and rapidity of theπ+π−system in the fiducial region defined as transverse momentum pT(π) > 0.2 GeV and pseudorapid-ity|η(π)| < 2.4. The production cross sections for the four resonant channels f0(500),ρ
0(770), f
0(980), and f2(1270) are extracted using a simple model. These results represent the first measurement of this process at the LHC collision energies of 5.02 and 13 TeV.
1 Introduction
The central exclusive production (CEP) process has been studied for a long time from both theoretical [1–7] and exper-imental [8–18] perspectives. In this process, both protons remain intact in the collision and a central system is pro-duced. The process is referred to as exclusive when no par-ticles other than the central system are produced. If one or both protons dissociate into a forward diffractive system, the process is called semiexclusive production. Various central systems can be produced in this process, likeπ+π−, K+K−, and 4π. In this paper, theπ+π−central system is measured. At the CERN LHC energies, the two dominant mechanisms ofπ+π−production via CEP are double pomeron exchange (DPE) and vector meson photoproduction (VMP), which are illustrated by the diagrams shown in Fig.1. The pomeron (P) is a color singlet object introduced to explain the rise of e-mail:cms-publication-committee-chair@cern.ch
the inelastic cross section at high collision energies [19,20]. The quantum numbers of the pomeron constrain the possi-ble central systems in DPE processes, whereas the photon exchange restricts the central system in VMP processes. By functioning as a quantum number filter, the CEP process is suitable to study low-mass resonances, which would be dif-ficult to study otherwise. Furthermore, DPE processes are also suitable to search for glueballs (bound states of gluons without valence quarks), because they provide a gluon-rich environment [21,22]. Another process that could contribute to the same final state is the two-photon fusionγγ →π+π−, which is expected to have a much smaller cross section than DPE and VMP processes and gives a negligible contribution [23].
The DPE process of pion pair production has two sub-categories: continuum and resonant production. In the case of continuum production, the pion pair is directly produced; thus the pairs have a nonresonant invariant mass spectrum. Resonant production means that an intermediate meson reso-nance is produced centrally, which manifests itself as a peak in the invariant mass distribution of the pion pair. Since the pomeron is a Regge trajectory running over states with quan-tum numbers JPC = {0++, 1++, 2++, . . . } and IG = 0+, the resonance is restricted to have JPC = {0++, 2++, 4++, . . . } and IG = 0+, where J is the total angular momen-tum, I is the isospin, P is the parity, C is the charge parity, and G= C (−1)I. The known particles [24] satisfying these criteria are the f0, f2,χc0,χc2,χb0, andχb2 resonances. The cross section for DPE (σπDPE+π−) can be calculated from the amplitude of continuum ( ADPE,C
(a) (b) (c)
Fig. 1 Diagrams of the dominant mechanisms forπ+π−production via CEP in proton-proton collisions: a continuum; b resonant double pomeron exchange; and c vector meson photoproduction
In VMP, one of the protons emits a virtual photon, which fluctuates into a quark-antiquark bound state and scatters from the proton via the pomeron exchange. The quan-tum numbers of the possible resonances are constrained by the quantum numbers of the pomeron and the pho-ton ( JPC = 1−−), leading to mesons with odd spin and the following quantum numbers JPC = {1−−, 3−−, . . . }. Resonances satisfying these conditions are ρ0, ω, φ, J/ψ, ψ(2S), and Υ, but only the ρ0 → π+π− decay has a significant branching fraction, since decays in this chan-nel are strongly suppressed in the case of φ, J/ψ, ψ(2S), and Υ according to the Okubo–Zweig–Iizuka rule [25–
27] and in the case of ω because of G-parity conservation [28].
This paper presents measurements of exclusive and semiexclusiveπ+π−total and differential cross sections as functions of invariant mass m(π+π−), transverse momen-tum pT(π+π−), and rapidity y(π+π−) of the pion pair, in a fiducial region defined by single pion transverse momen-tum pT(π) > 0.2 GeV and single pion pseudorapidity |η(π)| < 2.4. Because the outgoing protons are not tagged in this measurement, there is a residual contribution from semiexclusive production with all dissociation products out-side the |η| > 4.9 range. In the following, the exclusive and the residual semiexclusive contribution together will be referred to as central exclusive production. The data were recorded by CMS with beam conditions ensuring a small probability of multiple pp collisions in the same bunch cross-ing (pileup) in August 2015 at a center-of-mass energy of 13 TeV with luminosity 258μb−1and in November 2015 at 5.02 TeV with a luminosity of 522μb−1. The average num-ber of pp collisions in a bunch crossing was around 0.3– 0.5 for the 5.02 TeV and around 0.5 for the 13 TeV data sets.
2 The CMS detector
The central feature of the CMS apparatus is a superconduct-ing solenoid of 6 m internal diameter. Within the solenoid volume are a tracker, a lead tungstate crystal electromag-netic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections, covering the |η| < 3.0 region. Forward calorimeters extend the η coverage provided by the barrel and endcap detectors. Muons are measured in gas-ionization detectors embedded in the steel flux-return yoke outside the solenoid.
The silicon tracker measures charged particles within the range|η| < 2.5. It consists of 1440 silicon pixel and 15148 silicon strip detector modules and is located in the 3.8 T solenoid field. Three pixel barrel layers (PXB) are situated at radii of 4.4, 7.3, and 10.2 cm; PXB also has two pixel end-cap disks (PXF). The strip tracker consists of the innermost tracker inner barrel (TIB) and the tracker inner disks (TID), which are surrounded by the tracker outer barrel (TOB). It is completed by endcaps (TEC) on both sides. The barrel part of the strip tracker has a total of 10 layers at radii from 25 to 110 cm, whereas the endcap of the strip tracker con-sists of 12 layers. For charged particles with pT < 1 GeV and|η| < 1.4, the track resolutions are typically 1–2% in pT, and 90–300 and 100–350µ for the transverse and lon-gitudinal impact parameters, respectively [29]. The tracker provides an opportunity to identify charged particles with 0.3 < p < 2 GeV based on their specific ionization in the silicon detector elements [30].
The ECAL consists of 75 848 lead tungstate crystals, which provide coverage in|η| < 1.479 in the barrel region and 1.479 < |η| < 3.0 in the two endcap regions.
0.087 radians in azimuth (φ). In the η-φ plane, and for |η| < 1.48, the HCAL cells map onto 5×5 ECAL crystal arrays to form calorimeter towers projecting radially outwards from close to the nominal interaction point. At larger values of|η|, the towers are larger and the matching ECAL arrays contain fewer crystals.
The forward hadron (HF) calorimeter uses steel as an absorber and quartz fibers as the sensitive material. The two halves of the HF are located at 11.2 m from the interaction region, one at each end. Together they provide coverage in the range 3.0 < |η| < 5.2. Each HF calorimeter consists of 432 readout towers, containing long and short quartz fibers run-ning parallel to the beam. The long fibers run the entire depth of the HF calorimeter (165 cm, or approximately 10 interac-tion lengths), whereas the short fibers start at a depth of 22 cm from the front of the detector. By reading out the two sets of fibers separately, it is possible to distinguish showers gener-ated by electrons or photons, which deposit a large fraction of their energy in the long-fiber calorimeter segment, from those generated by hadrons, which typically produce, on average, nearly equal signals in both calorimeter segments.
The triggers used in this analysis are based on signals from the Beam Pick-up and Timing for eXperiments (BPTX) detectors [31]. The BPTX devices have a time resolution of less than 0.2 ns. They are located around the beam pipe at a distance of±175m from the nominal interaction point, and are designed to provide precise information on the bunch structure and timing of the proton beams.
A more detailed description of the CMS detector, together with a definition of the coordinate system used and the rele-vant kinematic variables, can be found in Ref. [32].
3 Monte Carlo simulations
Two kinds of Monte Carlo (MC) event generators are used in this analysis: inclusive and exclusive generators. The inclu-sive generators model the incluinclu-sive diffractive dissociation [33] and nondiffractive interactions, and are used to estimate the tracking efficiency, multiple reconstruction and misre-construction rates. The exclusive generators are used to gen-erate CEP events and to calculate the vertex correction fac-tors. There are no available MC event generators that produce exclusive scalar and tensor resonances via DPE, such as the production of f0(500), f0(980), and f2(1270) mesons.
Event samples are generated with various tunes for diffrac-tion and the underlying event:
– pythia 8.205 [34] with CUETP8M1 tune [35] and MBR model [36]: pythia 8 is an inclusive generator based on the Schuler and Sjöstrand model. It is capable of mod-eling a wide variety of physical processes, such as sin-gle diffractive (SD), double diffractive (DD), and
cen-tral diffractive (CD) dissociation, as well as nondiffrac-tive (ND) production [33]. The SD, DD, and ND events are generated with the CUETP8M1 tune. The Minimum Bias Rockefeller (MBR) model of pythia is based on the renormalized pomeron flux model and it is capable of generating SD, DD, ND and CD events.
– epos [37] with its LHC tune [38]: This inclusive generator is based on the Regge–Gribov phenomenology [39], and it models SD, DD, CD, and ND processes.
– starlight [40]: This event generator models photon-photon and photon-photon-pomeron interactions in pp and heavy ion collisions. The production ofρ0 mesons and their successive decay into two pions through the VMP pro-cess is simulated by starlight. For background studies, ωmesons are also generated with starlight and their decay simulated by pythia to theπ+π−π0final state. – dime mc 1.06 [5]: The dime mc software describes
con-tinuum π+π− production through DPE. The generator uses a phenomenological model based on Regge theory. Events are generated with the Orear-type off-shell meson form factors with parameters aor = 0.71 GeV−1 and bor = 0.91 GeV−1[5]. Furthermore, two additional MC samples are generated with an exponential form factor with bexp= 0.45 [5] and 1 GeV−2[1] to study the system-atic uncertainty in the measured resonance cross sections arising from uncertainties in the dime mc parametriza-tion.
All of the generated events are processed by a detailed Geant4simulation [41] of the CMS detector.
4 Event selection
The following triggers were employed:
– Zero bias: zero-bias events are selected by using either the BPTX detectors (13 TeV data) or the LHC clock sig-nal and the known LHC bunch structure (5.02 TeV data). Both methods provided zero-bias events.
– BPTX XOR: Here XOR stands for the exclusive OR logic, where only one BPTX is fired, corresponding to an incoming proton bunch from only one direction. This trigger was used in both 5.02 and 13 TeV data sets. – No-BPTX: There is no signal in the BPTX detectors,
col-Table 1 The value of calorimeter thresholds for different calorimeter constituents, used in the selection of exclusive events
Calorimeter Threshold [GeV] η coverage
ECAL barrel 0.6 |η| < 1.5
ECAL endcap 3.3 1.5 < |η| < 3.0
HCAL barrel 2.0 |η| < 1.3
HCAL endcap 3.8 1.3 < |η| < 3.0
HF 4.0 3.15 < |η| < 5.2
lisions between beam particles and residual gas molecules in the CMS beampipe (beam-gas background). The contri-bution from beam-gas collisions is negligible because there is no difference in the measured calorimeter tower energy distributions for the BPTX XOR and No-BPTX triggered events.
In the offline selections, it is required that the event has exactly two tracks, both of which satisfyχ2/ndf < 2 (where theχ2value is calculated based on the fitted trajectory and the measured tracker hits, and ndf is the number of degrees of freedom), pT > 0.2 GeV, and |η| < 2.4 to ensure high track reconstruction efficiency. Only events with oppositely charged (opposite-sign, OS) tracks are selected for analysis, whereas events with same-sign (SS) tracks are used in the background estimation.
Events with a single collision are selected by requiring the two tracks form a single reconstructed vertex subject to the constraint that |z1− z2| < 3 σ2 1 + σ 2 2, (2)
where z1and z2are the z coordinates of the closest approach of the reconstructed tracks to the beamline, andσ1andσ2are their corresponding uncertainties.
To select exclusive events, all calorimeter towers not matching the trajectories of the two tracks must have energy deposits below a threshold, which is defined in Table 1. A tower is matched to a track if the intersection of the extrapolated trajectory with the calorimeter surface is within three standard deviations inη and φ from the center of the tower. The threshold values are chosen to have a maximum 1% rejection of signal events resulting from the electronic noise of the calorimeters. Non-exclusive events might be also selected because of the lack of coverage in the eta gap between the HF and central calorimeters; these events are also taken into account in the background estimation pre-sented later in this paper.
Using all of the above listed event selection criteria, a total of 48 961 events were selected from the 5.02 TeV and 20 980 from the 13 TeV dataset.
5 Data analysis
5.1 Particle identification
Particle identification is used to select pion pairs by the mean energy loss (dE/dx) of particles in the silicon tracking detec-tors. The dE/dx values shown in the left panel of Fig.2are calculated by a second-order harmonic mean using only the strip detectors [42]: dE dx = 1 N N i=1 (ΔE/Δx)−2i −1 2 , (3)
where N is the number of energy loss measurements, ΔE/Δx is a single energy loss measurement per path length in one tracker module, and the sum runs over the strip detec-tors carrying energy loss measurements. The−2 exponent in this formula suppresses highΔE/Δx values arising from the highly asymmetricΔE/Δx Landau distribution, thus avoid-ing a bias in the estimate of the average dE/dx of the track. The track classification is achieved by fitting the mean energy loss distributions of tracks from low multiplicity (Ntrack ≤ 4) events with a sum of three Gaussian func-tions corresponding to pions, kaons, and protons. An exam-ple for such a fit is shown in the right panel of Fig.2. In the 0.3–2 GeV momentum range pions are selected from the ±3 standard deviation region of the corresponding Gaus-sian peak. This region is shown in the left panel of Fig.2. Tracks that have p < 0.3 or p > 2 GeV are assumed to be pions. The contamination from kaons and protons is estimated using the data-driven approach described in Sect.
5.3.
5.2 Corrections
Each event is weighted by several correction factors to com-pensate for the detector and reconstruction effects. The mul-tiplying factor is the product of four independent corrections: tracking, multiple reconstruction, vertex, and pileup correc-tion.
A tracking correction is used to correct for track recon-struction inefficiencies: Ctr= 1 εtr,1 1 εtr,2 , (4)
Fig. 2 Left: The distribution of the logarithm of the mean energy loss and absolute value of the momentum of tracks from low-multiplicity (Ntrack≤ 4) events collected at√s= 13 TeV. Theπ-selection region is
shown in the 0.3–2 GeV range. All tracks outside this momentum range
are identified as pions. Right: The fit of energy loss distributions in a given momentum bin with the sum of three Gaussian curves. Plots are similar for the 5.02 TeV data
εmrec, which is the probability for this situation to occur. In this case the correction factor takes the form
Cmrec= 1 1− εmrec,1
1
1− εmrec,2. (5)
The values ofεtr andεmrec are estimated as a function of η and pT using MC simulations. Their dependence on the track φ and the vertex position z-coordinate is integrated over. The simulated events are weighted such that the vertex z-coordinate distribution agrees with collision data.
The vertex correction Cvert accounts for events with an unreconstructed vertex. It is the reciprocal of the vertex effi-ciency, which is calculated using samples produced by the dime mcand starlight generators. The vertex efficiency has a slight dependence on the invariant mass of the track pair that is included when applying the vertex correction.
Some real CEP events are rejected because of pileup. To account for these lost events, a correction factor Cpufor the number of selected events can be computed. The CEP events are selected from bunch crossings with a single collision, so by assuming that the number of collisions follows a Poisson distribution, one can derive Cpu:
Cpu=
Nμ
Nμ exp (−μ) = exp (μ). (6)
Table 2 Correction factors
Type Range
Tracking 1.05–1.50
Multiple reconstruction 1.005–1.040
Vertex 1.05–1.33
Pileup 1.3–2.1
Here,μ is the average number of visible inelastic collisions, in a given bunch crossing, N is the total number of analyzed events. The value ofμ depends on the instantaneous lumi-nosity associated with individual bunch crossings, Lbunch, according to the following expression:
μ = σinel,visLbunch
f , (7)
whereσinel,vis is the visible inelastic pp cross section, f is the revolution frequency of protons, andLbunchis the average instantaneous luminosity at the given bunch crossing posi-tion for time periods of 23.3 s. The ratio ofσinel,visto f is obtained by fitting the fraction of events with no observed collisions as a function ofLbunch with the functional form A exp(−b Lbunch), where A and b are free parameters of the fit.
Fig. 3 The number of extra calorimeter towers over threshold in events containing an identified pion pair with opposite (left) and same (right) charge. The known contributions, denoted with the red hatched areas, are used to estimate the background in the zero bin of the opposite-sign
distribution, which is denoted by the blue hatched area. The error bars correspond to statistical uncertainties, whereas the error rectangle on the background denotes the 14% systematic uncertainty in the background normalization. Plots are similar for 5.02 TeV data
5.3 Background estimation
The main background contributions toπ+π− CEP are the multiparticle background and the exclusive K+K−/pp pro-duction. The multiparticle background in the selected exclu-sive sample consists of events with more than two particles created in the interaction, of which only two are observed because the additional particles yield energy deposits below the thresholds, or outside the acceptance. The SD, DD, ND, and CD processes with more than two centrally pro-duced particles belong to this contribution. A method based on control regions is used to estimate this multiparticle background. Control regions are selected in which events have at least two calorimeter towers above threshold, not matched to the two selected pions, with all the other selec-tion criteria satisfied. The distribuselec-tion of the number of events selected in this way as a function of the num-ber of extra towers with energy above threshold is shown in Fig. 3. The counts in the bins with 2, 3, 4, and 5 towers are used to estimate the background. The normal-ization factor is calculated using the following assump-tion:
Nmpart,SS(0 extra towers) Nmpart,SS(2–5 extra towers)
= Nmpart,OS(0 extra towers)
N (2–5 extra towers), (8)
Table 3 Checking the validity of Eq. (8) by comparing the true and predicted number of background events in inclusive MC samples Event generator Difference in normalization
epos (+11 ± 4)%
pythia8 CUETP8M1 (−5.5 ± 3)%
pythia8 MBR (+10 ± 4)%
where Nmpart,OS/SS is the number of multiparticle events with two OS or SS tracks. The validity of this assumption is checked by comparing the true and predicted number of background events in inclusive MC samples (Table3). The observed discrepancy reflects the differences between OS and SS events and is included as a systematic uncertainty in the estimate of the total number of multiparticle back-ground events, as discussed in Sect.5.4. With this formula and the fact that all SS events are multiparticle events because of charge conservation, it is possible to calculate the value of Nmhad,OS(0 towers), which is the number of multiparticle background events. The expected distribution of the multi-particle background is obtained using OS events with 2–5 extra calorimeter towers.
Fig. 4 Background distributions as functions of kinematic variables estimated by data-driven methods. The proton dissociation background is not shown here, since it is included via scaling of the final cross
sec-tion values. The error bars correspond to statistical uncertainties. The results for the 5.02 TeV data set are similar
Genuine exclusive K+K−and pp events, where both par-ticles are misidentified as pions, are included in the previous multiparticle background estimate. To correct for this contri-bution, the K/πratios are calculated in the exclusive events using tracks with p< 1 GeV. Similarly, the p/πratio is cal-culated in the same sample in the range 1 < p < 2 GeV. The K/π and p/π ratios are assumed to be 0.3+0.1−0.05 in the region p > 1 and p > 2 GeV, respectively [43]. Using
or p is a totally independent process. The final estimate of the exclusive K+K−and pp background normalization is calcu-lated as the average of the estimates obtained from assuming these two scenarios. According to these calculations, there is an 11% residual contribution of exclusive K+K−and pp events in the sample after the multiparticle background sub-traction. The background distributions of this contribution are calculated by using two-track OS exclusive events with at least one identified K±(Fig.4).
The estimated multiparticle and exclusive K+K−/pp background distributions, as functions of the main kinematic variables, are shown in Fig.4. These two background contri-butions are subtracted from the measured districontri-butions. The background subtracted spectra are divided by the integrated luminosity to obtain the differential cross sections.
5.4 Systematic uncertainties
Systematic uncertainties in the measured cross sections orig-inate from various sources. These include reconstruction effects, particle identification, correction factors, background estimation, and the luminosity estimation. The uncertainty assigned to the tracking efficiency in the case of a single track is 3.9% [29], which corresponds to 7.8% uncertainty for two tracks. Furthermore, the uncertainty in the multiple reconstruction rate for a single track is also 3.9%, which prop-agates to a maximum of 0.4% uncertainty in the cross section for two tracks, which is neglected in the analysis. Misrecon-structed tracks bias the sample in two ways: either a CEP event is rejected if a third misreconstructed track is found, or an event is identified as CEP with a misreconstructed and a genuine track. This source of systematic uncertainty is esti-mated to be 1% for a single track, which is the maximal mis-reconstruction rate calculated using inclusive MC samples in the kinematic region ( pT(π) > 0.2 GeV and |η(π)| < 2.4) of the analysis. Since the probability to have two or more misre-constructed tracks in these low-multiplicity events is negligi-ble, the final uncertainty remains 1%. From the comparison of the dime mc and starlight simulations, the uncertainty of the vertex correction is estimated to be 1%.
The systematic uncertainty in the pileup correction fac-tor for a single event is calculated from only the systematic uncertainties in the luminosity measurement that do not affect its overall normalization. Indeed, the normalization-related systematic uncertainties are compensated in the exponential fit described in Sect.5.2. The uncertainties that do not affect the normalization are estimated to be 1.6% and 1.5% for 5.02 [44] and 13 TeV [45] data, respectively. These values propagate to a 1% uncertainty in the pileup correction factor for a single event. After adding up all the selected events, the pileup uncertainty becomes smaller than 0.1%, which is neglected in the following.
The measured signal yield is affected by the uncertainty arising from the two effects associated with calorimeter noise and veto inefficiency caused by the adopted energy thresh-olds. A genuine CEP event can be erroneously discarded if the calorimeter noise appears above the energy thresholds used in the veto. Conversely a nonCEP event can pass the final selection if the extra particles pass the veto requirements. In the HF, these uncertainties are estimated by varying the calorimeter energy thresholds by±10% [46]. The resulting uncertainty is estimated to be 3% for both the 5.02 and 13 TeV data sets. Similarly, the ECAL and HCAL thresholds are var-ied by±5% [47,48], which results in a 1% uncertainty in the corrected yields at both energies.
The systematic uncertainty estimation of the multiparticle background is done by varying the control region used in the background estimation procedure: 1–2, 2–9, and 5–9 extra towers. The estimate of the systematic uncertainty in the mul-tiparticle background normalization is 10%. Additionally, a 10% uncertainty is added to this value quadratically, taking into account the deviations shown in Table3; thus the final uncertainty in the multiparticle background normalization is 14%. After subtracting this contribution, this propagates to systematic uncertainties depending on the invariant mass, transverse momentum and rapidity of the pion pair. The mul-tiparticle background estimation uncertainty varies between 10–20% below 1500 MeV. Over 1500 MeV the uncertainty varies between 20–60%, because the signal versus back-ground ratio is much smaller. The average uncertainty, used as the systematic uncertainty of the total cross section, is 15%.
Table 4 The sources and average values of systematic uncertainties, used as the systematic uncertainty of the total cross section
Source Average value
Tracking efficiency 7.8%
Misreconstructed tracks 1%
Vertex 1%
HF energy scale 3%
ECAL and HCAL energy scale 1%
Multiparticle background 15%
Exclusive K+K−and pp background 6%
Total w/o int. luminosity 18.3%
+ Integrated luminosity 2.3%
All of the systematic uncertainties listed above are the same for the 5.02 and 13 TeV data sets. Additionally, the systematic uncertainty in the integrated luminosity is 2.3% [44,45]. The average values of the systematic uncertainties are summarized in Table4. The total systematic uncertainty is obtained by adding the individual contributions in quadra-ture. All systematic uncertainty contributions are considered fully correlated across invariant mass bins.
6 Results
The differential cross sections are calculated from the selected events as functions of the invariant mass, trans-verse momentum, and rapidity of the pion pair. These are shown in Fig. 5 with the generator-level predictions from the starlight and dime mc generators, normalized to their cross sections. The MC generators provide an incomplete description of the available data, since they do not model the f0(500), f0(980), and f2(1270) resonances as mentioned in Sect.3.
There is a peak at 800 MeV, which corresponds to the ρ0(770) resonance. Since its quantum numbers IG(JPC) =
1+(1−−) are forbidden in DPE processes, the ρ0 mesons must be produced in VMP processes. The sharp drop vis-ible around 1000 MeV is expected from previous measure-ments [11,16] and can be attributed to the quantum mechan-ical interference of f0(980) with the continuum contribution. There is a prominent peak at 1200–1300 MeV, which corre-sponds to the f2(1270) resonance with I
G
(JPC
) = 0+(2++) quantum numbers. This resonance is produced via a DPE process.
Both dime mc and starlight underestimate the mea-sured spectrum as these MC event generators do not model the forward dissociation of protons.
The total cross section of the CEP process with two pions in the final state in the kinematic region pT(π) > 0.2 GeV
and |η(π)| < 2.4 is obtained by integrating the observed spectra in this region:
σpp→ppπ+π−(√s= 5.02 TeV) = 32.6 ± 0.7 (stat)
± 6.0 (syst) ± 0.8 (lumi) μb, (9) σpp→ppπ+π−(√s= 13 TeV) = 33.7 ± 1.0 (stat)
± 6.2 (syst) ± 0.8 (lumi) μb. (10) Below, it is demonstrated that the measured invariantπ+π− mass spectrum is well-described by the sum of the contin-uum distributions obtained from the dime mc model and four dominant resonances, modeled here by Breit-Wigner func-tions. In the fitting procedure the quantum mechanical inter-ference effect and the detector resolution are also included.
The following fit function is used: f(m) = G(m − m; σ ) |AρRBW0 (m)|2 + |Af0(500)RBW (m)eiφf0(500)m+ Af0(980) RBW (m )eiφf0(980)m + Af2 RBW(m )eiφf2m+ b Bdime (m)|2 dm. (11) Here G(m; σ) is a Gaussian distribution with variance σ and zero mean, Bdime(m) is the nonresonant background esti-mated from the dime mc using the Orear-type form fac-tor, and b is a scale factor for the continuum contribution, andφf0(500),φf0(980), and φf2 are phases that characterize interference effects. The AiRBW(m) is the relativistic Breit– Wigner amplitude, which can be written as [49]:
AiRBW,J (m) = Ai m MiΓ (m) m2− Mi2+ i MiΓ (m) , (12) Γ (m) = Γi Mi m m2− 4m2π Mi2− 4m 2 π 2 J+1 2 , (13)
where Ai, Mi, andΓi are the yield, mass, and width of the
resonance, respectively, mπis the mass of charged pions, and J is the total angular momentum of the resonance. Accord-ing to Ref. [2], the magnitude of the interference between the DPE and VMP processes is around 1%, therefore no inter-ference term is used betweenρ0and DPE resonances. The convolution with the Gaussian distribution models the mass resolution of the detector.
0 500 1000 1500 2000 2500
) [MeV]
−π
+π
m(
0 0.5 1 1.5 2 2.5 3 3.5 4b / (50 MeV)]μ
[
dm
σ
d
) > 0.2 GeV π ( T p )| < 2.4 π ( η | Data Syst. unc. Res. + bkg. fit Dime MC scaled Resonant peaks /ndf = 81/36 2 χ(5.02 TeV)
-1b
μ
522
CMS
0 500 1000 1500 2000 2500) [MeV]
−π
+π
m(
0 0.5 1 1.5 2 2.5 3 3.5 4b / (50 MeV)]μ
[
dm
σ
d
) > 0.2 GeV π ( T p )| < 2.4 π ( η | Data Syst. unc. Res. + bkg. fit Dime MC scaled Resonant peaks /ndf = 52/36 2 χ(13 TeV)
-1b
μ
258
CMS
Fig. 6 Fit to the measured cross section with the sum of four interfering relativistic Breit–Wigner functions convolved with a normal distribu-tion (to account for the the experimental resoludistribu-tion of the detector) for
the 5.02 (left) and 13 TeV (right) data sets. The error bars correspond to statistical, whereas the open boxes correspond to systematic uncer-tainties
Table 5 Cross sections of the resonant processes in the pT(π) >
0.2 GeV, |η(π)| < 2.4 fiducial region, extracted from the simple model
fit using the sum of the continuum distribution obtained from the dime
mcmodel and four dominant resonances. The luminosity-related
uncer-tainties are included in the systematic unceruncer-tainties. The starlight predictions for pp→ ppρ0→ ppπ+π−processes are 2.3 and 3.0
μb for 5.02 and 13 TeV, respectively, which is compatible with the fit
results
Resonance σpp→ppX→ppπ+π−[μb]
√s= 5.02 TeV √s= 13 TeV
f0(500) 2.8 ± 1.4 (stat) ± 2.2 (syst) 2.2 ± 0.8 (stat) ± 1.3 (syst)
ρ0(770) 4.7 ± 0.9 (stat) ± 1.3 (syst) 4.3 ± 1.3 (stat) ± 1.5 (syst) f0(980) 0.5 ± 0.1 (stat) ± 0.1 (syst) 1.1 ± 0.4 (stat) ± 0.3 (syst)
f2(1270) 3.6 ± 0.6 (stat) ± 0.7 (syst) 4.2 ± 0.9 (stat) ± 0.8 (syst)
taken into account by repeating the fit with a mass resolution varying from 9 to 14 MeV. The resulting systematic uncer-tainty is 7–8% for the yield of f0(980) and around 1–2% for the yields of the f0(500),ρ
0(770), and f
2(1270) resonances. The impact of the uncertainty in the multiparticle (exclusive K+K−and pp ) background yield is included by varying the background normalization in the fit by±14% (±72%).
The masses and widths ofρ0(770) and f2(1270) reso-nances are fixed to the values of Ref. [24]. The mass and width of f0(500) and f0(980) are fixed according to the results from the most advanced calculations using dispersion relations [50].
The fits are also performed with the mass and width of f0(500) and f0(980) varied according to their
uncer-tainties [24] and the resulting variation in the cross sec-tion of the resonances is added in quadrature to the other systematic uncertainty contributions. Furthermore the fit is repeated with the two other dime mc settings and the varia-tion in the cross secvaria-tion is taken as an addivaria-tional systematic uncertainty and added in quadrature to the other uncertain-ties.
The above simple model fit also provides values for the cross sections of the resonances; these are obtained by inte-grating the fitted squared amplitudes from the dipion thresh-old (2mπ) to Mi+ 5Γi: σres i = Mi+5Γi 2mπ |A 2 RBW,i(m)|dm. (14)
The fits are shown in Fig.6and the cross sections are sum-marized in Table5.
7 Summary
The cross sections for central exclusive pion pair produc-tion have been measured in pp collisions at 5.02 and 13 TeV center-of-mass energies. Exclusive events are selected by vetoing additional energy deposits in the calorimeters and by requiring two oppositely charged pions identified via their mean energy loss in the tracker detectors. These events are used together with correction factors to obtain invariant mass, transverse momentum, and rapidity distributions of the π+π− system. The measured total exclusiveπ+π− produc-tion cross secproduc-tion is 32.6±0.7 (stat)±6.0 (syst)±0.8 (lumi) and 33.7±1.0 (stat)±6.2 (syst)±0.8 (lumi) μb for 5.02 and 13 TeV, respectively. The observed mass spectrum exhibits resonant structures, which can be fitted with a simple model containing four interfering Breit-Wigner functions, corre-sponding to the f0(500),ρ
0(770), f
0(980), and f2(1270) res-onances, and a continuum contribution modeled by the dime mc. The exclusive production cross sections are extracted from this fit. The obtained cross sections ofρ0(770) produc-tion are higher than the starlight model predicproduc-tion, which can be explained by the presence of semiexclusive production which is not modeled by the starlight generator.
Acknowledgements We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and per-sonnel of the Worldwide LHC Computing Grid for delivering so effec-tively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, PUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NKFIA (Hun-gary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI, and FEDER (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 752730, and 765710 (European Union); the Leventis Foundation; the A.P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science – EOS” – be.h project n. 30820817; the Beijing Municipal Science & Technology
Commis-sion, No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Deutsche Forschungsge-meinschaft (DFG) under Germany’s Excellence Strategy – EXC 2121 “Quantum Universe” – 390833306; the Lendület (“Momentum”) Pro-gram and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA research grants 123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary); the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foun-dation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Sci-ence and Higher Education, the National SciSci-ence Center (Poland), con-tracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/ E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Ministry of Science and Education, grant no. 14.W03.31.0026 (Russia); the Tomsk Polytechnic University Com-petitiveness Enhancement Program and “Nauka” Project FSWW-2020-0008 (Russia); the Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia María de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fel-lowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Founda-tion (USA).
Data Availability Statement This manuscript has no associated data or the data will not be deposited. [Authors’ comment: Release and preser-vation of data used by the CMS Collaboration as the basis for publi-cations is guided by the CMS policy as written in its document “CMS data preservation, re-use and open access policy” (https://cms-docdb. cern.ch/cgi-bin/PublicDocDB/RetrieveFile?docid=6032&filename= CMSDataPolicyV1.2.pdf&version=2).]
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CMS Collaboration
Yerevan Physics Institute, Yerevan, Armenia
A. M. Sirunyan†, A. Tumasyan
Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck1, R. Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki
Institute for Nuclear Problems, Minsk, Belarus
V. Drugakov, V. Mossolov, J. Suarez Gonzalez
Universiteit Antwerpen, Antwerpen, Belgium
M. R. Darwish, E. A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, A. Lelek, M. Pieters, H. Rejeb Sfar, H. Van Haevermaet, P. Van Mechelen, S. Van Putte, N. Van Remortel
Vrije Universiteit Brussel, Brussel, Belgium
F. Blekman, E. S. Bols, S. S. Chhibra, J. D’Hondt, J. De Clercq, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L. Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs
Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, L. Favart, A. Grebenyuk, A. K. Kalsi, J. Luetic, A. Popov, N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom, Q. Wang
Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, I. Khvastunov2, C. Roskas, D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis
Université Catholique de Louvain, Louvain-la-Neuve, Belgium
O. Bondu, G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A. Giammanco, G. Krintiras, V. Lemaitre, A. Magitteri, K. Piotrzkowski, J. Prisciandaro, A. Saggio, M. Vidal Marono, P. Vischia, J. Zobec
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
F. L. Alves, G. A. Alves, G. Correia Silva, C. Hensel, A. Moraes, P. Rebello Teles
Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L. M. Huertas Guativa, H. Malbouisson, J. Martins5, D. Matos Figueiredo, M. Medina Jaime6, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima,
W. L. Prado Da Silva, L. J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E. J. Tonelli Manganote3, F. Torres Da Silva De Araujo, A. Vilela Pereira
Universidade Estadual Paulistaa, Universidade Federal do ABCb, São Paulo, Brazil
S. Ahujaa, C. A. Bernardesa, L. Calligarisa, T. R. Fernandez Perez Tomeia, E. M. Gregoresb, D. S. Lemos, P. G. Mercadanteb, S. F. Novaesa, Sandra S. Padulaa
Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia, Bulgaria
A. Aleksandrov, G. Antchev, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov, M. Shopova, G. Sultanov
University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov
Beihang University, Beijing, China
W. Fang7, X. Gao7, L. Yuan
Department of Physics, Tsinghua University, Beijing, China
Z. Hu, Y. Wang
Institute of High Energy Physics, Beijing, China
M. Ahmad, G. M. Chen, H. S. Chen, M. Chen, C. H. Jiang, D. Leggat, H. Liao, Z. Liu, S. M. Shaheen8, A. Spiezia, J. Tao, E. Yazgan, H. Zhang, S. Zhang8, J. Zhao
State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China
A. Agapitos, Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S. J. Qian, D. Wang
Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, L. F. Chaparro Sierra, C. Florez, C. F. González Hernández, M. A. Segura Delgado
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia
D. Giljanovi´c, N. Godinovic, D. Lelas, I. Puljak, T. Sculac
Faculty of Science, University of Split, Split, Croatia
Z. Antunovic, M. Kovac
Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, S. Ceci, D. Ferencek, K. Kadija, B. Mesic, M. Roguljic, A. Starodumov9, T. Susa
University of Cyprus, Nicosia, Cyprus
M. W. Ather, A. Attikis, E. Erodotou, A. Ioannou, M. Kolosova, S. Konstantinou, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski, D. Tsiakkouri
Charles University, Prague, Czech Republic
M. Finger10, M. Finger Jr.10, A. Kveton, J. Tomsa
Escuela Politecnica Nacional, Quito, Ecuador
E. Ayala
Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin
Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
M. A. Mahmoud11,12, Y. Mohammed11
National Institute of Chemical Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R. K. Dewanjee, K. Ehataht, M. Kadastik, M. Raidal, C. Veelken
Department of Physics, University of Helsinki, Helsinki, Finland
Helsinki Institute of Physics, Helsinki, Finland
F. Garcia, J. Havukainen, J. K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T. Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi
Lappeenranta University of Technology, Lappeenranta, Finland
T. Tuuva
IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J. L. Faure, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup, E. Locci, J. Malcles, J. Rander, A. Rosowsky, M. Ö. Sahin,
A. Savoy-Navarro13, M. Titov
Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris, Paris, France
C. Amendola, F. Beaudette, P. Busson, C. Charlot, B. Diab, R. Granier de Cassagnac, I. Kucher, A. Lobanov,
C. Martin Perez, M. Nguyen, C. Ochando, P. Paganini, J. Rembser, R. Salerno, J. B. Sauvan, Y. Sirois, A. Zabi, A. Zghiche
Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram14, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E. C. Chabert, C. Collard, E. Conte14, J.-C. Fontaine14, D. Gelé, U. Goerlach, M. Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove
Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France
S. Gadrat
Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, C. Camen, N. Chanon, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, B. Ille, Sa. Jain, F. Lagarde, I. B. Laktineh, H. Lattaud, M. Lethuillier, L. Mirabito, S. Perries, V. Sordini, G. Touquet, M. Vander Donckt, S. Viret
Georgian Technical University, Tbilisi, Georgia
T. Toriashvili15
Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze10
RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany
C. Autermann, L. Feld, M. K. Kiesel, K. Klein, M. Lipinski, D. Meuser, A. Pauls, M. Preuten, M. P. Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer
RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, M. Erdmann, S. Erdweg, T. Esch, B. Fischer, R. Fischer, S. Ghosh, T. Hebbeker, K. Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, G. Mocellin, S. Mondal, S. Mukherjee, D. Noll, A. Novak, T. Pook, A. Pozdnyakov, T. Quast, M. Radziej, Y. Rath, H. Reithler, M. Rieger, A. Schmidt, S. C. Schuler, A. Sharma, S. Thüer, S. Wiedenbeck
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, W. Haj Ahmad16, O. Hlushchenko, T. Kress, T. Müller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl17
Deutsches Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, C. Asawatangtrakuldee, P. Asmuss, I. Babounikau, H. Bakhshiansohi, K. Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D. Bertsche, A. A. Bin Anuar, K. Borras18, V. Botta, A. Campbell, A. Cardini, P. Connor, S. Consuegra Rodríguez, C. Contreras-Campana, V. Danilov, A. De Wit, M. M. Defranchis, C. Diez Pardos, D. Domínguez Damiani, G. Eckerlin, D. Eckstein, T. Eichhorn, A. Elwood, E. Eren, E. Gallo19, A. Geiser,
J. M. Grados Luyando, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, N. Z. Jomhari, H. Jung, A. Kasem18, M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker, W. Lange, T. Lenz, J. Leonard, J. Lidrych, K. Lipka, W. Lohmann20, R. Mankel, I.-A. Melzer-Pellmann, A. B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich,
P. Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A. Vagnerini, M. Van De Klundert, G. P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev, R. Zlebcik
University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A. Ebrahimi, A. Fröhlich, C. Garbers, E. Garutti, D. Gonzalez, P. Gunnellini, J. Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange, T. Lange, A. Malara, D. Marconi, J. Multhaup, M. Niedziela, C. E. N. Niemeyer, D. Nowatschin, A. Perieanu, A. Reimers, O. Rieger, C. Scharf, P. Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück, F. M. Stober, M. Stöver, B. Vormwald, I. Zoi
Karlsruher Institut fuer Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, T. Berger, E. Butz, R. Caspart, T. Chwalek, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, M. Giffels, P. Goldenzweig, A. Gottmann, M. A. Harrendorf, F. Hartmann17, U. Husemann, S. Kudella, S. Mitra, M. U. Mozer, Th. Müller, M. Musich, A. Nürnberg, G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, H. J. Simonis, R. Ulrich, M. Weber, C. Wöhrmann, R. Wolf
Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, P. Asenov, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G. Paspalaki
National and Kapodistrian University of Athens, Athens, Greece
M. Diamantopoulou, G. Karathanasis, P. Kontaxakis, A. Panagiotou, I. Papavergou, N. Saoulidou, A. Stakia, K. Theofilatos, K. Vellidis
National Technical University of Athens, Athens, Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis
University of Ioánnina, Ioannina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K. Manitara, N. Manthos, I. Papadopoulos, J. Strologas, F. A. Triantis, D. Tsitsonis
MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary
M. Bartók21, M. Csanad, P. Major, K. Mandal, A. Mehta, M. I. Nagy, G. Pasztor, O. Surányi, G. I. Veres
Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath22, F. Sikler, T. Á. Vámi, V. Veszpremi, G. Vesztergombi†
Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi21, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
P. Raics, D. Teyssier, Z. L. Trocsanyi, B. Ujvari
Eszterhazy Karoly University, Karoly Robert Campus, Gyongyos, Hungary
T. F. Csorgo, W. J. Metzger, F. Nemes, T. Novak
Indian Institute of Science (IISc), Bangalore, India
S. Choudhury, J. R. Komaragiri, P. C. Tiwari
National Institute of Science Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati24, C. Kar, G. Kole, P. Mal, V. K. Muraleedharan Nair Bindhu, A. Nayak25, S. Roy Chowdhury, D. K. Sahoo24, S. K. Swain
Panjab University, Chandigarh, India
S. Bansal, S. B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R. Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, K. Sandeep, S. Sharma, J. B. Singh, A. K. Virdi, G. Walia
University of Delhi, Delhi, India
Saha Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj26, M. Bharti26, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep26, D. Bhowmik, S. Dey, S. Dutta, S. Ghosh, M. Maity27, K. Mondal, S. Nandan, A. Purohit, P. K. Rout, A. Roy, G. Saha, S. Sarkar, T. Sarkar27, M. Sharan, B. Singh26, S. Thakur26
Indian Institute of Technology Madras, Madras, India
P. K. Behera, P. Kalbhor, A. Muhammad, P. R. Pujahari, A. Sharma, A. K. Sikdar
Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, D. K. Mishra, P. K. Netrakanti, L. M. Pant, P. Shukla
Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M. A. Bhat, S. Dugad, G. B. Mohanty, N. Sur, RavindraKumar Verma
Tata Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, S. Karmakar, S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo, S. Sawant
Indian Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A. Rastogi, S. Sharma
Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani27, E. Eskandari Tadavani, S. M. Etesami27, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi
University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald
INFN Sezione di Baria, Università di Barib, Politecnico di Baric, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, L. Fiorea, A. Gelmia,b, G. Iasellia,c, M. Incea,b, S. Lezkia,b, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G. Selvaggia,b, L. Silvestrisa,
R. Vendittia, P. Verwilligena
INFN Sezione di Bolognaa, Università di Bolognab, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-Giacomellia,b, R. Campaninia,b,
P. Capiluppia,b, A. Castroa,b, F. R. Cavalloa, S. C. Cioccaa, G. Codispotia,b, M. Cuffiania,b, G. M. Dallavallea, F. Fabbria, A. Fanfania,b, E. Fontanesi, P. Giacomellia, C. Grandia, L. Guiduccia,b, F. Iemmia,b, S. Lo Meoa,29, S. Marcellinia, G. Masettia, F. L. Navarriaa,b, A. Perrottaa, F. Primaveraa,b, A. M. Rossia,b, T. Rovellia,b, G. P. Sirolia,b, N. Tosia
INFN Sezione di Cataniaa, Università di Cataniab, Catania, Italy
S. Albergoa,b,30, S. Costaa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b,30, C. Tuvea,b,30
INFN Sezione di Firenzea, Università di Firenzeb, Florence, Italy
G. Barbaglia, R. Ceccarellia,b, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b, G. Latino, P. Lenzia,b, M. Meschinia, S. Paolettia, L. Russoa,31, G. Sguazzonia, D. Stroma, L. Viliania
INFN Laboratori Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, D. Piccolo
INFN Sezione di Genovaa, Università di Genovab, Genoa, Italy
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b
INFN Sezione di Milano-Bicoccaa, Università di Milano-Bicoccab, Milan, Italy
